Conference proceeding
Application of parallelized analogical planning to engineering design
Proceedings of the 3rd international conference on industrial and engineering applications of artificial intelligence and expert systems, Vol.2, pp.914-922
IEA/AIE '90
06/01/1990
Handle:
https://hdl.handle.net/2376/116658
Abstract
Analogical planning provides a means of solving engineering problems where other machine learning methods fail. Unlike many machine learning paradigms, analogy does not require numerous previous examples or a rich domain theory. Instead, analogical reasoning utilizes knowledge of solved problems in similar domains, adapting the knowledge to the current problem. Unfortunately, the analogical planning task is an expensive one. While the process of forming correspondences between a known and a new problem is complex, the problem of selecting a base case for the analogy is virtually intractable.
This paper addresses the issue of efficiently forming analogical plans. The ANAGRAM planning system is described, which takes advantage of the massively parallel architecture of the Connection Machine to perform base selection and map formation. This approach makes analogical planning a tractable task, in fact sublinear in the size of the plans.
This paper describes the ANAGRAM system and its parallel algorithms. The paper also presents a theoretical analysis and empirical results of testing the system on a large database of plans from the domain of automatic programming.
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Details
- Title
- Application of parallelized analogical planning to engineering design
- Creators
- Diane Cook
- Publication Details
- Proceedings of the 3rd international conference on industrial and engineering applications of artificial intelligence and expert systems, Vol.2, pp.914-922
- Academic Unit
- Electrical Engineering and Computer Science, School of
- Series
- IEA/AIE '90
- Publisher
- ACM
- Identifiers
- 99900547334201842
- Language
- English
- Resource Type
- Conference proceeding